GenerateTiePointsByCrossCorrelation

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ENVIGenerateTiePointsByCrossCorrelationTask

This task performs automatic tie point generation using cross correlation as a similarity measure. This method works well for general purposes, especially registering images with similar modality (e.g., registering optical images with optical images).

The following diagram shows where this task belongs within an image-to-image registration workflow:

Jin, Xiaoying, and Robert Schafer. Method and system for automatic registration of images. Exelis, Inc., assignee; now owned by Harris Corporation. U.S. Patent No. 9,245,201 (issued January 26, 2016).

Example

This example uses sample images from the Image Registration tutorial. The files are available on the ENVI Resource DVD under the /image_reg directory or from the ENVI Tutorials web page. Click the "ENVI Tutorial Data" hyperlink. Copy the files to your local drive.

Properties marked as "Set" are those that you can set to specific values. You can also retrieve their current values any time. Properties marked as "Get" are those whose values you can retrieve but not set.

INPUT_RASTER1 (required)

INPUT_RASTER2 (required)

INPUT_SEED_TIEPOINTS (optional)

This is a reference to an ENVITiePointSet object with input seed tie points.

INTEREST_OPERATOR (optional)

Specify the interest operator to use to identify feature points. The default value is Forstner.

Forstner: Obtains and analyzes the gray scale gradient matrix between one pixel and its adjacent pixels. The Forstner operator is typically better for image matching than the Moravec operator.

Moravec: Seearches for gray scale value differences between one pixel and its adjacent pixels. The Moravec operator is typically faster than the Forstner operator.

Harris: Improves upon Moravec by using the auto-correlation matrix and avoids using discrete directions and shifts.

MATCHING_SCORES (optional)

The normalized cross-correlation between the matching windows (specified with the MATCHING_WINDOW property) in both input images is computed as the matching score. This value is a double-precision array in the form [number of tie points].

This is an advanced property designed for users who want more control over filtering tie points by matching scores. See Example: Matching Scores for a code example.

MATCHING_WINDOW (optional)

Specify the matching window size used for computing the matching score between the two images. The default value is 61.

MINIMUM_MATCHING_SCORE (optional)

Specify a floating-point value indicating the minimum matching score. Tie points with a matching score less than the minimum value are considered outliers and are removed. If the image pairs have a large parallax, it is likely that the matching score is low and you should decrease this value. The default value is 0.6. To register images with different modalities (e.g., registering SAR with optical images), set the minimum matching score to a lower value.

OUTPUT_TIEPOINTS

This is a reference to an ENVITiePointSet object with the output tie points.

OUTPUT_TIEPOINTS_URI (optional)

Specify a string with the fully qualified path and filename for OUTPUT_TIEPOINTS.

REQUESTED_NUMBER_OF_TIEPOINTS (optional)

Specify the requested number of tie points. The default value is 121.

SEARCH_WINDOW (optional)

Specify the tolerance for the search range. The default value is 255.

Example: Matching Scores

The folloing script shows how to use the MATCHING_SCORES property to filter tie points using matching scores: